4 citations · 11 across the 7 of their papers we have counts for
5 papers · 1 filter
Advances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challenge
Vladyslav Zalevskyi, Thomas Sanchez, Misha Kaandorp +67
Accurate fetal brain tissue segmentation and biometric analysis are essential for studying brain development in utero. The FeTA Challenge 2024 advanced automated fetal brain MRI an…
Comparative Benchmarking of Failure Detection Methods in Medical Image Segmentation: Unveiling the Role of Confidence Aggregation
Maximilian Zenk, David Zimmerer, Fabian Isensee +4
Semantic segmentation is an essential component of medical image analysis research, with recent deep learning algorithms offering out-of-the-box applicability across diverse datase…
Real-World Federated Learning in Radiology: Hurdles to overcome and Benefits to gain
Markus R. Bujotzek, Ünal Akünal, Stefan Denner +17
Objective: Federated Learning (FL) enables collaborative model training while keeping data locally. Currently, most FL studies in radiology are conducted in simulated environments…
ValUES: A Framework for Systematic Validation of Uncertainty Estimation in Semantic Segmentation
Kim-Celine Kahl, Carsten T. Lüth, Maximilian Zenk +2
Uncertainty estimation is an essential and heavily-studied component for the reliable application of semantic segmentation methods. While various studies exist claiming methodologi…
Why is the winner the best?
Matthias Eisenmann, Annika Reinke, Vivienn Weru +122
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…